模拟吉布提共和国土地利用和土地覆被变化的选定驱动变量:一项来自半干旱地区的研究

S. Pandit, S. Shimada, Timothy Dube
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摘要

摘要本研究旨在将驱动变量与土地利用变化模型(LCM)相结合,在吉布提共和国土地利用变化的背景下,考虑可能出现的 "一切照旧 "情景,探讨驱动变量对自然环境的影响。分析了 1990 年和 2012 年有关土地利用、土地覆被 (LULC) 的二手数据,并采用与二手数据相同的方法(谷歌地球引擎 (GEE) 中的随机森林分类)生成了 2022 年地图,以进行验证。利用八个关键驱动变量为吉布提未来(2035 年)的合理土地覆被建模。将土地覆被模型的统计输出和变化图与历史变化估计值和模拟情景进行了比较。从 1990 年到 2022 年的分析凸显了城市化、环境因素和经济发展所带来的重大土地利用和植被变化。贫瘠土地和灌木丛占主导地位,而建筑区和水体则明显扩大。城市化、农业和气候变化导致植被退化,红树林减少,建筑密集区增加。在此期间,水体也有所扩大。根据 2035 年土地利用、土地利用变化和林业地图的预测,城市规模将进一步扩大,这凸显了采取可持续土地管理措施的必要性。总之,全面的土地利用规划、跨学科方法和利益相关者的参与被认为是应对吉布提的社会经济和环境挑战以及走向可持续未来的关键。这些模拟结果为地区政府在城市化和人口增长趋势下制定战略政策和评估资源利用管理行动提供了宝贵的见解。
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Selected Driver Variables for the Simulation of Land-Use and Land-Cover Change for the Republic of Djibouti: A Study from Semi-Arid Region
Abstract. This study aims to integrate driver variables with a land use change model (LCM) to explore their impact on the natural environment within the context of land-use changes in the Republic of Djibouti, considering possible Business-as-usual scenarios. Secondary data from 1990 and 2012 on land use land cover (LULC) were analyzed, with a 2022 map generated by adopting the same method of secondary data used (random forest classification in Google Earth Engine (GEE)) for validation. Eight key driver variables were utilized to model plausible future land cover (2035) for Djibouti. Statistical outputs and change maps from the LCM were compared to gauge historical change estimates and simulated scenarios. Analysis from 1990 to 2022 highlights significant land use and cover changes spurred by urbanization, environmental factors, and economic development. Barren land and bushland dominated, while built-up areas and water bodies expanded notably. Urbanization, agriculture, and climate change contributed to vegetation degradation, with declines in mangroves and increases in built-up areas. Water bodies also expanded during this period. Projections from the 2035 LULC map anticipate further urban expansion, underscoring the need for sustainable land management practices. In conclusion, comprehensive land-use planning, interdisciplinary approaches, and stakeholder engagement are deemed critical for addressing Djibouti's socio-economic and environmental challenges and steering towards a sustainable future. These simulated results offer valuable insights for regional governments to frame strategic policies and assess management actions for resource utilization amidst urbanization and population growth trends.
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